The Internet world makes increasing use of XML-based technologies. In multimedia data indexing and retrieval, the MPEG-7 standard for Multimedia Description Scheme is specified using XML. The flexibility of XML allows users to define other markup semantics for special contexts, construct data-centric XML documents, exchange standardized data between computer systems, and present data in different applications. In this paper, the Inverted Image Indexing paradigm is presented and modeled using XML Schema.
KEYWORDS: Visualization, Databases, Data storage, Binary data, Information visualization, Classification systems, Multimedia, Data modeling, Image classification, Video
The management of visual object databases is an essential function of visual information systems, and the efficient retrieval the associated data objects is vital to operation of these systems. In this paper, we use the number of visual objects retrieved per second as a measure of the throughput of visual object databases. An efficient storage organization technique for executing visual queries is studied: we group similar visual objects together as visual object groups and store each visual object group at consecutive physical locations. We propose a structured high-level indexing system that can cater for the similarity criteria employed in the application domain. Our system incorporates classification hierarchies into an indexing superstructure of metadata, context and content, using high- level content descriptions. Database performance is quantified using queuing analyses, and we show that our technique is able to significantly increase throughput and database performance.
Inverted file indexing and its compression have proved to be highly successful for free-text retrieval. Although the 'inverted' nature of the data structure provides an efficient mechanism for searching key words or terms in large documents, for image retrieval, the application of inverted files to the title, caption, or description of the images are not sufficient. One must be able to index and retrieve images based on the visual contents. Many content-based image retrieval techniques are used for the images as a whole picture. Analogous to free-text retrieval, a novel technique, called inverted image indexing and compression, is proposed in this paper. Similar to works in a document, each image can have multiple areas which are perceived to be meaningful visual contents. These areas are selected by users and then undergo two processes: automatic signature generation based on wavelet signatures, and users specification of high-level contents using ternary fact model. The contents in compressed form are inserted into an inverted image file. The concept of composite bitplane signature is also introduced.
A new feature indexing scheme for binary images is proposed. Using the structures of the conjugate classification of the hexagonal grid, ten intrinsically geometric invariant clusters are identified to partition a binary image into ten feature cluster images. The numbers of feature points in feature images are evaluated. Using the ten integers, a probability model is defined to generate quantitative measurements for feature indexing. This provides intrinsic feature indexing sets for rapid retrieval images based on their contents. Two vectors of twelve probability measurements are used to describe different images in varying sizes and sample pictures and their feature indices are illustrated.
The problem of content-based retrieval of images from electronic media is especially acute in contexts where the subject-matter of the images is very general. The Birkbeck system attempts to overcome the limitations of traditional keyword systems, which provide a random and undifferentiated listing of objects in a picture, by using an augmented entity-relationship model in the data-modeling process. The interface, which allows successive query reformulation, emulates some of those aspects of browsing so important in picture collections. The subject- matter of the picture is described in terms of its objects, their attributes and the relationships existing between them. The form of the description (for both storage and retrieval) is defined by the grammar of the Picture Description Language and the Picture Query Language. Descriptions which are input to the system are parsed to generate SQL statements for the RDBMS which stores the data. Pictures relevant to the user''s enquiry are retrieved and displayed in miniature for rapid consultation. To refine further the set of pictures selected the system allows query modification, which is supported by a thesaurus. Higher rates of recall and precision are achieved than are normally possible in image storage and retrieval.
Conference Committee Involvement (8)
Multimedia Content Access: Algorithms and Systems IV
21 January 2010 | San Jose, California, United States
Multimedia Content Access: Algorithms and Systems III
21 January 2009 | San Jose, California, United States
Multimedia Content Access: Algorithms and Systems II
30 January 2008 | San Jose, California, United States
Multimedia Content Access: Algorithms and Systems
31 January 2007 | San Jose, CA, United States
Internet Imaging VII
18 January 2006 | San Jose, California, United States
Internet Imaging VI
19 January 2005 | San Jose, California, United States
Internet Imaging V
19 January 2004 | San Jose, California, United States
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